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How Social Q&A Sites are Changing Knowledge Sharing in Open Source Software Communities
"... Historically, mailing lists have been the preferred means for coordinating development and user support activities. With the emergence and popularity growth of social Q&A sites such as the StackExchange network (e.g., StackOverflow), this is beginning to change. Such sites offer different socio- ..."
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Historically, mailing lists have been the preferred means for coordinating development and user support activities. With the emergence and popularity growth of social Q&A sites such as the StackExchange network (e.g., StackOverflow), this is beginning to change. Such sites offer different socio-technical incentives to their participants than mailing lists do, e.g., rich web environments to store and manage content col-laboratively, or a place to showcase their knowledge and ex-pertise more visibly to peers or potential recruiters. A key difference between StackExchange and mailing lists is gam-ification, i.e., StackExchange participants compete to obtain reputation points and badges. Using a case study of R, a popular data analysis software, in this paper we investigate how mailing list participation has evolved since the launch of StackExchange. Our main contribution is assembling a joint data set from the two sources, in which participants in both the r-help mailing list and StackExchange are identi-fiable. This allows for linking their activities across the two resources and also over time. With this data set we found that user support activities are showing a strong shift away from r-help. In particular, mailing list experts are mi-grating to StackExchange, where their behaviour is different. First, participants active both on r-help and on StackEx-change are more active than those who focus exclusively on only one of the two. Second, they provide faster answers on StackExchange than on r-help, suggesting they are moti-vated by the gamified environment. To our knowledge, our study is the first to directly chart the changes in behaviour of specific contributors as they migrate into gamified environ-ments, and has important implications for knowledge man-agement in software engineering. Author Keywords Crowdsourced knowledge; social Q&A; mailing lists; open
Wisdom in the Social Crowd: an Analysis of Quora
"... Efforts such as Wikipedia have shown the ability of user communities to collect, organize and curate information on the Internet. Recently, a number of question and answer (Q&A) sites have successfully built large growing knowledge repositories, each driven by a wide range of questions and answe ..."
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Efforts such as Wikipedia have shown the ability of user communities to collect, organize and curate information on the Internet. Recently, a number of question and answer (Q&A) sites have successfully built large growing knowledge repositories, each driven by a wide range of questions and answers from its users community. While sites like Yahoo Answers have stalled and begun to shrink, one site still going strong is Quora, a rapidly growing service that augments a regular Q&A system with social links between users. Despite its success, however, little is known about what drives Quora’s growth, and how it continues to connect visitors and experts to the right questions as it grows. In this paper, we present results of a detailed analysis of Quora using measurements. We shed light on the impact of three different connection networks (or graphs) inside Quora, a graph connecting topics to users, a social graph connecting users, and a graph connecting related questions. Our results show that heterogeneity in the user and question graphs are significant contributors to the quality of Quora’s knowledge base. One drives the attention and activity of users, and the other directs them to a small set of popular and interesting questions.
Superposter behavior in MOOC forums
- In Proceedings of the first ACM conference on Learning@ scale conference
, 2014
"... Discussion forums, employed by MOOC providers as the pri-mary mode of interaction among instructors and students, have emerged as one of the important components of on-line courses. We empirically study contribution behavior in these online collaborative learning forums using data from 44 MOOCs host ..."
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Discussion forums, employed by MOOC providers as the pri-mary mode of interaction among instructors and students, have emerged as one of the important components of on-line courses. We empirically study contribution behavior in these online collaborative learning forums using data from 44 MOOCs hosted on Coursera, focusing primarily on the highest-volume contributors—“superposters”—in a forum. We explore who these superposters are and study their en-gagement patterns across the MOOC platform, with a focus on the following question—to what extent is superposting a positive phenomenon for the forum? Specifically, while su-perposters clearly contribute heavily to the forum in terms of quantity, how do these contributions rate in terms of quality, and does this prolific posting behavior negatively impact con-tribution from the large remainder of students in the class? We analyze these questions across the courses in our dataset, and find that superposters display above-average engagement across Coursera, enrolling in more courses and obtaining bet-ter grades than the average forum participant; additionally, students who are superposters in one course are significantly more likely to be superposters in other courses they take. In terms of utility, our analysis indicates that while being nei-ther the fastest nor the most upvoted, superposters ’ responses are speedier and receive more upvotes than the average fo-rum user’s posts; a manual assessment of quality on a sub-set of this content supports this conclusion that a large frac-tion of superposter contributions indeed constitute useful con-tent. Finally, we find that superposters ’ prolific contribution behavior does not ‘drown out the silent majority’—high su-perposter activity correlates positively and significantly with higher overall activity and forum health, as measured by total contribution volume, higher average perceived utility in terms of received votes, and a smaller fraction of orphaned threads. Author Keywords massive open online course; MOOC; education; Coursera;
Learning about social learning in MOOCs: From statistical analysis to generative model
, 2013
"... We study user behavior in the courses offered by a major Massive Online Open Course (MOOC) provider during the summer of 2013. Since social learning is a key element of scalable education in MOOCs and is done via online discussion forums, our main focus is in understanding forum activities. Two sali ..."
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We study user behavior in the courses offered by a major Massive Online Open Course (MOOC) provider during the summer of 2013. Since social learning is a key element of scalable education in MOOCs and is done via online discussion forums, our main focus is in understanding forum activities. Two salient features of MOOC forum activities drive our research: 1. High decline rate: for all courses studied, the volume of discussions in the forum declines continuously throughout the duration of the course. 2. High-volume, noisy discussions: at least 30 % of the courses produce new discussion threads at rates that are infeasible for students or teaching staff to read through. Furthermore, a substantial portion of the discussions are not directly course-related. We investigate factors that correlate with the decline
CQARank: Jointly Model Topics and Expertise in Community Question Answering
, 2013
"... Community Question Answering (CQA) websites, where peo-ple share expertise on open platforms, have become large reposi-tories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retriev ..."
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Cited by 9 (0 self)
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Community Question Answering (CQA) websites, where peo-ple share expertise on open platforms, have become large reposi-tories of valuable knowledge. To bring the best value out of these knowledge repositories, it is critically important for CQA services to know how to find the right experts, retrieve archived similar questions and recommend best answers to new questions. To tackle
Answering questions about unanswered questions of stack overflow
- Proc. Tenth Int. Workshop on Mining Software Repositories. – IEEE Press, 2013. – P
"... Abstract—Community-based question answering services ac-cumulate large volumes of knowledge through the voluntary services of people across the globe. Stack Overflow is an ex-ample of such a service that targets developers and software engineers. In general, questions in Stack Overflow are answered ..."
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Abstract—Community-based question answering services ac-cumulate large volumes of knowledge through the voluntary services of people across the globe. Stack Overflow is an ex-ample of such a service that targets developers and software engineers. In general, questions in Stack Overflow are answered in a very short time. However, we found that the number of unanswered questions has increased significantly in the past two years. Understanding why questions remain unanswered can help information seekers improve the quality of their questions, increase their chances of getting answers, and better decide when to use Stack Overflow services. In this paper, we mine data on unanswered questions from Stack Overflow. We then conduct a qualitative study to categorize unanswered questions, which reveals characteristics that would be difficult to find otherwise. Finally, we conduct an experiment to determine whether we can predict how long a question will remain unanswered in Stack Overflow. Index Terms—Stack Overflow; question-answer; prediction;
Slow Search: Information Retrieval without Time Constraints
- In Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval
, 2013
"... ABSTRACT Significant time and effort has been devoted to reducing the time between query receipt and search engine response, and for good reason. Research suggests that even slightly higher retrieval latency by Web search engines can lead to dramatic decreases in users' perceptions of result q ..."
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ABSTRACT Significant time and effort has been devoted to reducing the time between query receipt and search engine response, and for good reason. Research suggests that even slightly higher retrieval latency by Web search engines can lead to dramatic decreases in users' perceptions of result quality and engagement with the search results. While users have come to expect rapid responses from search engines, recent advances in our understanding of how people find information suggest that there are scenarios where a search engine could take significantly longer than a fraction of a second to return relevant content. This raises the important question: What would search look like if search engines were not constrained by existing expectations for speed? In this paper, we explore slow search, a class of search where traditional speed requirements are relaxed in favor of a high quality search experience. Via large-scale log analysis and user surveys, we examine how individuals value time when searching. We confirm that speed is important, but also show that there are many search situations where result quality is more important. This highlights intriguing opportunities for search systems to support new search experiences with high quality result content that takes time to identify. Slow search has the potential to change the search experience as we know it.
Analysis of the reputation system and user contributions on a question answering website: Stackoverflow
- in ASONAM, 2013
"... Abstract—Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide a significant portion of the helpful answers, and so identifying users that have the potent ..."
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Abstract—Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide a significant portion of the helpful answers, and so identifying users that have the potential of becoming strong contributers is an important task for owners of such communities. We present a study of the popular Q&A website Stack-Overflow (SO), in which users ask and answer questions about software development, algorithms, math and other technical topics. The dataset includes information on 3.5 million questions and 6.9 million answers created by 1.3 million users in the years 2008-2012. Participation in activities on the site (such as asking and answering questions) earns users reputation, which is an indicator of the value of that user to the site. We describe an analysis of the SO reputation system, and the participation patterns of high and low reputation users. The contributions of very high reputation users to the site indicate that they are the primary source of answers, and especially of high quality answers. Interestingly, we find that while the majority of questions on the site are asked by low reputation users, on average a high reputation user asks more questions than a user with low reputation. We consider a number of graph analysis methods for detecting influential and anomalous users in the underlying user interaction network, and find they are effective in detecting extreme behaviors such as those of spam users. Lastly, we show an application of our analysis: by considering user contributions over first months of activity on the site, we predict who will become influential long-term contributors. I.
Routing Questions for Collaborative Answering in Community Question Answering
, 2013
"... Community Question Answering (CQA) service enables its users to exchange knowledge in the form of questions and answers. By allowing the users to contribute knowledge, CQA not only satisfies the question askers but also provides valuable references to other users with similar queries. Due to a larg ..."
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Community Question Answering (CQA) service enables its users to exchange knowledge in the form of questions and answers. By allowing the users to contribute knowledge, CQA not only satisfies the question askers but also provides valuable references to other users with similar queries. Due to a large volume of questions, not all questions get fully answered. As a result, it can be useful to route a question to a potential answerer. In this paper, we present a question routing scheme which takes into account the answering, commenting and voting propensities of the users. Unlike prior work which focuses on routing a question to the most desirable expert, we focus on routing it to a group of users- who would be willing to collaborate and provide useful answers to that question. Through empirical evidence, we show that more answers and comments are desirable for improving the lasting value of a question-answer thread. As a result, our focus is on routing a question to a team of compatible users. We propose a recommendation model that takes into account the compatibility, topical expertise and availability of the users. Our experiments over a large real-world dataset shows the effectiveness of our approach over several baseline models.
